DQN Q-values are static
It is likely converging to a far worse local optimum from which it can't recover, so yes I would guess if all else is the same, that is where the issue would be. I would first try to adjust hyperparameters from a static seed for weight initialization.  ε and α, are likely good places to start. 

If that fails, adjust some architecture params like the number of units or layers in the network as well as the starting seed value. 

You seemingly have run into a core problem at the heart of ML research which is reproducibility, which is often predicated by initialization.